电影分级准确预测的决策树算法

K. Pradeep, C. R. TintuRosmin, Sherly Susana Durom, G. Anisha
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引用次数: 3

摘要

在本文中,我们的目标是通过系统地分析决策树算法,找到一种准确的算法,用于实现利用Weka工具的信息挖掘系统,以依赖于系统的几个重要品质来预测电影的成就或失望。首先计算每个属性的权重,然后使用决策树算法对属性进行组合计算,计算出该电影的权重。这里我们主要在三种决策树算法上尝试实现这个想法。J48算法,随机森林,hoeffding树。在这里,我们试图找到一部赚钱电影的关键因素。这个模型通过电影的品质或属性来帮助发现即将上映的电影的评级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Decision Tree Algorithms for Accurate Prediction of Movie Rating
In this paper, we aim to find an accurate algorithm for implementing information mining systems utilizing Weka tool to foresee the achievement or disappointment of motion pictures dependent on a few important qualities with respect to system by systematically analyzing decision tree algorithms. The weightage for each attribute is calculated in the first stage, and then weightage of that movie is calculated by combined calculation of attributes using decision tree algorithms. Here we are trying to implement this idea on mainly three decision tree algorithms. J48 algorithm, Random Forest, Hoeffiding tree. Here, we try to find key factors for a profitable movie. This model assists with discovering the rating of the upcoming motion picture through qualities or attributes of that movie.
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